Graph-without-cut: An ideal graph learning for image segmentation

30th AAAI Conference on Artificial Intelligence, AAAI 2016

Volumn , Issue , 2016, Pages 1188-1194

  Gao, Lianli ^a   Song, Jingkuan ^b   Nie, Feiping ^c   Zou, Fuhao ^d   Sebe, Nicu ^b   Shen, Heng Tao ^a,e  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF TRENTO   (Italy)

^c NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^d HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^e UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GRAPHIC METHODS; MATRIX ALGEBRA;

CONNECTED COMPONENT; GRAPH SIMILARITY; GRAPH-BASED IMAGE SEGMENTATIONS; LAPLACIAN MATRICES; SEGMENTATION PERFORMANCE; STATE-OF-THE-ART PERFORMANCE; UNSUPERVISED IMAGE SEGMENTATION; VISUAL INFORMATION;

IMAGE SEGMENTATION;

EID: 84994636856     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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